Systems and methods for generating contextually relevant device protections

ABSTRACT

Systems and methods are disclosed herein that can detect use of a consumer electronics device and that can generate and offer insurance or protection plans that measure, account, and adjust for the use of the consumer electronics device and consumer tendencies while using the consumer electronics device.

FIELD

The present invention relates generally to a consumer electronicsdevice. More particularly, the present invention relates to systems andmethods that detect use of the consumer electronics device.

BACKGROUND

Many consumer electronics devices are sold at price points that areconsidered expensive to an average consumer. As a result, the averageconsumer sometimes chooses to purchase a protection or other insuranceplan to protect the consumer electronics device and reimburse theconsumer for replacing or repairing the consumer electronics device whenlost or damaged.

While many consumers commonly purchase insurance or protections plans,known insurance or protection plans are conventionally based on a retailprice of the consumer electronics device, a cost to replace the consumerelectronics device, or a cost to repair the consumer electronics device.However, known insurance or protection plans fail to account for use ofthe consumer electronics device or consumer tendencies while using theconsumer electronics device.

In view of the above, there exists a need for systems and methods forgenerating and offering insurance or protection plans that measure,account, and adjust for use of the consumer electronics device andconsumer tendencies while using the consumer electronics device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a system in accordance with disclosedembodiments;

FIG. 2 is a flow diagram of a method for detecting whether anelectronics device has been dropped in accordance with disclosedembodiments;

FIG. 3 is a graph plotting accelerometer measurements in accordance withdisclosed embodiments;

FIG. 4 is a graph plotting a tendency to drop a device in accordancewith disclosed embodiments;

FIG. 5 is a flow diagram of a method for adjusting risk in accordancewith disclosed embodiments;

FIG. 6 is a flow diagram of a method for adjusting risk and generatingwarnings in accordance with disclosed embodiments;

FIG. 7 is a graph plotting device depreciation in accordance withdisclosed embodiments;

FIG. 8 is a flow diagram of a method for accounting for devicedepreciation in accordance with disclosed embodiments;

FIG. 9 is a flow diagram of a method for accounting for devicedurability in accordance with disclosed embodiments; and

FIG. 10 is a flow diagram of a method for generating a protection planbased on device diagnostics in accordance with disclosed embodiments.

DETAILED DESCRIPTION

While this invention is susceptible of an embodiment in many differentforms, there are shown in the drawings and will be described herein indetail specific embodiments thereof with the understanding that thepresent disclosure is to be considered as an exemplification of theprinciples of the invention. It is not intended to limit the inventionto the specific illustrated embodiments.

Embodiments disclosed herein include systems and methods that can detectuse of a consumer electronics device and systems and methods that cangenerate and offer insurance or protection plans that measure, account,and adjust for the use of the consumer electronics device and consumertendencies while using the consumer electronics device.

In some embodiments, systems and methods disclosed herein can receive orretrieve data from sensors included within the consumer electronicsdevice, analyze the data, and determine whether the data indicates thatthe consumer electronics device has been dropped. For example, in someembodiments, systems and methods disclosed herein can determine whetherthe data from an accelerometer included within the consumer electronicsdevice indicates that acceleration of the consumer electronics device isconsistent with the consumer electronics device being dropped, such asthe data both exceeding a first threshold value and dropping below asecond threshold value within a predetermined period of time or the datainitially dropping below the second threshold value, subsequentlyexceeding the first threshold value, and subsequently dropping below thesecond threshold value within the predetermined period of time.Additionally or alternatively, in some embodiments, systems and methodsdisclosed herein can determine whether the data from a gyroscopeincluded within the consumer electronics device indicates that arotation and an orientation of the consumer electronics device isconsistent with the consumer electronics device being dropped andstrongly impacting a surface.

In some embodiments, systems and methods disclosed herein can identifyactivities related to the consumer electronics device that posepotential risk of damage to the consumer electronics device. Forexample, in some embodiments, systems and methods disclosed herein canidentify the activities that pose the potential risk of damage to theconsumer electronics device based on location data of the consumerelectronics device, intended location data of the consumer electronicsdevice, or intended events to be attended by a user of the consumerelectronics device.

In some embodiments, systems and methods disclosed herein can monitoruser interactions with the consumer electronics device, including theuser interactions or a lack of the user interactions with applicationsexecuted by the consumer electronics device, to determine a potentialrisk to the consumer electronics device or other items protected by aninsurance or protection plan. In some embodiments, systems and methodsdisclosed herein can transmit an audible or visual warning message tothe user indicative of the user interactions identified as posing thepotential risk.

In some embodiments, systems and methods disclosed herein can identify areplacement cost percentage for the consumer electronics device based ona depreciated value of the consumer electronics device and generate andoffer a discounted insurance or protection plan when the replacementcost percentage exceeds a predetermined threshold value.

In some embodiments, systems and methods disclosed herein can identify adurability index rating for the consumer electronics device and generateand offer a discounted insurance or protection plan when the durabilityindex rating exceeds a predetermined threshold value. In someembodiments, systems and methods disclosed herein can identify thedurability index rating based on extensive testing of various makes andmodels of consumer electronics devices.

In some embodiments, systems and methods disclosed herein can execute adiagnostics test on the consumer electronics device, determine whetherany components of the consumer electronics device are non-functional orbroken, and generate and offer a discounted insurance or protection planwhen a predetermined number of the components are identified asnon-functional. In some embodiments, a value of the discounted insuranceor protection plan can be based on which of the components is identifiedas non-functional and, based on past policy claims data, how often thatnon-functioning component is broken.

FIG. 1 is a block diagram of a system 100 in accordance with disclosedembodiments and can implement the methods disclosed herein. As seen, thesystem 100 can include a consumer electronics device 3 that can beoperated by a user 1 and that can execute a software application 2. Insome embodiments, the software application 2 can communicate with andreceive or retrieve data from one or more sensors 4 included within theconsumer electronics device 3. In some embodiments, the consumerelectronics device 3 can include a smartphone, a tablet, or a laptopcomputer. When the consumer electronics device 3 is a smartphone, theconsumer electronics device can include up to eight of the sensors 4,including one or more of a touchscreen, an accelerometer, a gyroscope, amagnetometer, a global positioning (GPS) system, a barometer, an ambientlight sensor, a proximity sensor, and a fingerprint sensor. Additionallyor alternatively, in some embodiments, the sensors 4 can include one ormore cameras, which can collect the data when the software 2 includesvideo analytics software.

In some embodiments, the software application 2 can be stored andexecuted on the consumer electronics device 3. Alternatively, in someembodiments, the software application 2 can be web-based and canretrieve the data from the sensors 4 when the consumer electronicsdevice 3 navigates to a website universal resource locator (URL)associated with the software application 2 or at periodic intervalsidentified by the software application 2.

In some embodiments, the software application 2 can generate a user riskprofile 5 based on the data received from the sensors 4 and save theuser risk profile 5 in a database device. For example, in someembodiments, the software application 2 can use the data from thesensors 4 to determine whether the consumer electronics device 3 hasbeen dropped by the user 1 a predetermined number of times thatindicates a propensity for dropping the consumer electronics device 3.Responsive thereto, the software application 2 can generate the userrisk profile 5 to indicate that the user 1 has a propensity to drop theconsumer electronics device 3, and, therefore, is associated with apredetermined level of risk to insure.

In some embodiments, the software application 2 and the consumerelectronics device 3 can transmit the user risk profile 5 to aprotection and insurance offering system 7 via a network connection,such as a LTE, 4G, WiFi, or any other Internet-based connection, and insome embodiments, the protection and insurance offering system 7 caninclude a cloud-based server, which can be accessible at a predeterminedURL. In some embodiments, the protection and insurance offering system 7can also receive or retrieve input data 6 from other sources. Forexample, the input data 6 can include identifications of locations thatpresent an increased risk to the safety of the consumer electronicsdevice 3, identifications of times and dates of events that present anincreased risk to the safety of the consumer electronics device 3,identifications of past interactions of the user 1 with another device,or identifications of any other factors that may impact the riskassociated with the user 1 owning and using the consumer electronicsdevice 3.

Based on the user risk profile 5 and the input data 6, the protectionand insurance offering system 7 can generate a risk based policyoffering 8 that is customized to the user and the consumer electronicsdevice 3. For example, in some embodiments, the risk based policyoffering 8 can include a custom price to insure the consumer electronicsdevice 3 for the user 1, and in some embodiments, the risk based policyoffering 8 can include terms and a scope of protection for an insuranceor protection plan associated with the user 1 and the consumerelectronics device 3. In some embodiments, the risk based policyoffering 8 can include a provision in a terms of service associated withthe risk based policy offering 8 requiring that the software application2 be installed on the consumer electronics device 2 at all times duringthe life of the risk based policy offering 8 and that removal of thesoftware application 2 from the consumer electronics device will voidinsurance protection associated with the risk based policy offering 8.

As disclosed herein, a common and constant risk to the consumerelectronics device 3 is that the user 1 will drop the consumerelectronics device 3, thereby damaging the consumer electronics device3. For example, if the user 1 drops the consumer electronics device 3from a sufficient height and in a specific manner, then a screen of theconsumer electronics device 3 may shatter. Thus, an important factormeasured by the software application 2 and included in the user riskprofile 5 is when and how often the user 1 drops the consumerelectronics device 3.

In this regard, the software application 2 can identify a trauma eventeach time the consumer electronics device 3 is dropped from a heightthat ends in a hard impact, and the software application 2 can use thetrauma event to create the user risk profile 5. In some embodiments, thesoftware application 2 can communicate with the user 1, such as bygenerating a notification message (e.g. email notification, pushnotification) that includes one or more suggested proactive actions toprevent future drops. For example, the one or more suggested proactiveactions may include the user 1 purchasing a shock-absorbing case for theconsumer electronics device 3, a screen protector for the consumerelectronics device, or gripping strips that increase an amount offriction on a housing of the consumer electronics device 3 while beingheld by the user 1. In some embodiments, the notification message mayinclude one or more reasons for the suggested proactive action, such asdata that suggests the user 1 drops the consumer electronics device 3more than average.

As disclosed herein, the software application 2 can identify when theconsumer electronics device 3 has been dropped. For example, in someembodiments, the software application 2 can monitor the data from thesensors 4, such as the accelerometer, to determine whether the consumerelectronics device 3 has been dropped. In some embodiments, the softwareapplication 2 can identify an impact level of the consumer electronicsdevice 3 being dropped to differentiate between a damage-inducing dropwhen the consumer electronics device 3 impacts a hard surface (e.g. acement floor) and a harmless drop when the consumer electronics device 3impacts a soft surface (e.g. a couch). In some embodiments, the softwareapplication 2 can validate the impact level using the data collectedfrom sensors 4, such as the accelerometer or the gyroscope.

FIG. 2 is a flow diagram of a method 200 for detecting whether theconsumer electronics device 3 has been dropped in accordance withdisclosed embodiments. As seen, the method 200 can include starting abackground service, as in 3-1. For example, the background service canbe started by installing the software application 2 on the consumerelectronics device 3 for continually monitoring the data from thesensors 4 to detect conditions indicative of a drop. In someembodiments, the background service may be unnoticeable to the user 1during regular use of the consumer electronics device 3.

The method 200 can also include setting lower and upper threshold valuesand a time interval, as in 3-2. In some embodiments, the lower and upperthreshold values and the time interval can be predetermined, and in someembodiments, the upper threshold can be greater than the lowerthreshold. For example, the upper threshold value can be set to anacceleration value corresponding with a height at which the consumerelectronics device 3 must be dropped to qualify as a damage-inducingdrop. Additionally or alternatively, in some embodiments, the lower andupper threshold values can be based on a type of the consumerelectronics device 3 on which the software application 2 is installed.For example, an iPhone 8 Plus may be heavier than an iPhone 8 so, whendropped, a force of impact for the iPhone 8 Plus may be higher than theiPhone 8. As such, the software application 2 installed on the iPhone 8Plus may set the upper threshold value higher than the softwareapplication 2 installed on the iPhone 8 sets the upper threshold value.Additionally or alternatively, in some embodiments, the upper and lowerthreshold values can be identified from the data from the sensors 4,including acceleration values measured by the accelerometer, angularvelocity values measured by the gyroscope, and/or orientation valuesmeasured by the gyroscope and the magnetometer. In any embodiment, thelower and upper threshold values can be set at values that facilitateidentifying drops that follow the same general pattern discussed herein.

The method 200 can also include the software application 2 determiningwhether the data from the accelerometer is indicative of a drop, thatis, whether the data indicates that an acceleration of the consumerelectronics device 3 exceeded the upper threshold value and subsequentlyfell below the lower threshold value within the time interval or whetherthe data indicates that the acceleration of the consumer electronicsdevice 3 initially fell below the lower threshold value, subsequentlyexceeded the upper threshold value, and subsequently fell below thelower threshold value, as in 3-3. In some embodiments, the accelerometercan include a tri-axial accelerometer with three axes (x-axis, y-axis,and z-axis) for measuring the data in three directions, and the datafrom the accelerometer can be measured in meters per second squared.When the accelerometer is the tri-axial accelerometer, the softwareapplication 2 can calculate a geometric mean of the data associated withthe three axes as follows: |A_(T)|=sqrt(a_(x) ², a_(y) ², a_(z) ²). Whenthe conditions of 3-3 have not been met, the software application 2 canrepeat 3-3. However, when the conditions of 3-3 have been met, themethod 200 can continue to 3-4.

Pursuant to the method 200, FIG. 3 is a graph 300 plotting accelerometermeasurements in accordance with disclosed embodiments and identifies theupper threshold value 302, the lower threshold value 304, and the dataindicative of a drop 306. As known by those of ordinary skill in theart, the data from the accelerometer can include the force of gravity(e.g. 9.81 m/s²). Accordingly, when the consumer electronics device 3 isstationary on a surface, the data from the accelerometer can be 9.81.However, when the consumer electronics device is falling downwards, thedata from the accelerometer can be 0. In this regard and as seen in FIG.3 , during the drop, the data from the accelerometer can initially fallbelow the lower threshold value 304 (e.g. accelerometer data=0 duringfree fall), subsequently exceed the upper threshold value 302 (e.g.accelerometer data=36 upon impacting a surface and bouncing off thesurface), and subsequently fall below the lower threshold value 304(e.g. accelerometer data=0 during free fall after bouncing off thesurface) within the time interval (e.g. 20 ms).

In some embodiments, after initially falling below the lower thresholdvalue 304, when the data from the accelerometer subsequently exceeds anintermediate threshold value that is below the upper threshold value302, the method 200 can determine that the consumer electronics device 3was dropped on a soft surface and, therefore, that the drop washarmless.

The method 200 can also include the software application 2 determiningwhether the drop concluded with an impact exceeding an impact thresholdvalue, as in 3-4. For example, in some embodiments, the method 200 canidentify an impact level of the consumer electronics device 3 beingdropped to differentiate between a damage-inducing drop when theconsumer electronics device 3 impacts a hard surface and a harmless dropwhen the consumer electronics device 3 impacts the soft surface. In thisregard, in some embodiments, the method 200 can validate the drop withthe data from the sensors 4, such as the data from the gyroscopeindicative of the rotation and/or the orientation of the consumerelectronics device 3 in azimuth (angle around the x-axis), pitch (anglearound the y-axis), and roll (angle around the z-axis) directions(^(θ)X, ^(θ)Y, ^(θ)Z). In some embodiments, after the data from theaccelerometer exceeds the upper threshold value, the softwareapplication 2 can calculate a geometric mean of the rotation of theconsumer electronics device 3 in degrees per second as follows:

=sqrt(

). Then, the software application 2 can confirm that the drop was adamage-inducing drop when the geometric mean of the rotation and theorientation exceeds the impact threshold value. In some embodiments, theimpact threshold value can be set based on rotation and orientationvalues of the consumer electronics device 3 impacting a hard surfaceduring a drop and/or dropping and inducing damage, wherein such valuescan be identified via modeling and testing of consumer electronicsdevices.

When the method 200 confirms that the drop was a damage-inducing drop,the method 200 can continue as in 3-5. However, when the method 200fails to confirm that the drop was a damage-inducing drop, the method200 can continue as in 3-3, and the software application 2 can confirmthat the drop was a harmless drop.

Finally, the method 200 can include the software application 2registering the drop on a cloud server, such as the protection andinsurance offering system 7, as in 3-5. In some embodiments, registeringthe drop can include the software application 2 updating a risk profile5 for the user 1 and the consumer electronics device 3. In this regard,FIG. 4 is a graph 400 plotting a tendency to drop a device in accordancewith disclosed embodiments and identifies four drops over a period oftime.

In some embodiments, the software application 2 can set a thrownthreshold value that can be lower than the lower threshold value. Inthese embodiments, when the data from the accelerometer falls below thethrown threshold value, the software application 2 can determine thatthe consumer electronics device 3 has been thrown, an event that may notbe protected by the risk based policy offering 8. Additionally oralternatively, the software application 2 can determine that theconsumer electronics device 3 has been thrown upward when the data fromthe accelerometer increased before initially falling below the lowerthreshold value.

When the software application 2 determines that the user 1 has apropensity to drop the consumer electronics device 3 (e.g. a number ofdrops within a time period exceeds a predetermined threshold value), theprotection and insurance offering system 7 can generate a notificationmessage to the consumer electronics device 3 that includes an offer tothe user 1 to purchase a case or a screen protector and that can beaccompanied by data illustrative of the user 1 having the propensity todrop the consumer electronics device 3. In addition, the protection andinsurance offering system 7 can increase a price of the risk basedpolicy offering 8 in response to determining that the user 1 has thepropensity to drop the consumer electronics device 3 and notify the user1 as such.

FIG. 5 is a flow diagram of a method 500 for adjusting risk inaccordance with disclosed embodiments, for example, by generating a riskprofile for the user 1 based on user events and user activities that mayaffect the risk involved with insuring or protecting the consumerelectronics device 3.

As seen, the method 500 can include starting an event detection process,as in 4-1. In some embodiments, the event detection process can includea background service that operates in conjunction with the backgroundservice described in connection with FIG. 2 . After beginning the eventdetection process, the method 500 can include the software application 2or the protection and insurance offering system 7 identifying the userevents and the user activities, as in 4-2, and retrieving identifiedrisk scenarios from an event monitoring database, as in 4-3, todetermine whether any of the user events and the user activities matchesany of the identified risk scenarios, as in 4-4. If no matches areidentified, as in 4-4, then the method 500 can include the softwareapplication 2 continuing to monitor for the user events and the useractivities, as in 4-2, and retrieve the identified risk scenarios, as in4-3. However, when the method 500 identifies a match between one of theuser events and the user activities and one of the identified riskscenarios, the method 500 can include the software application 2registering the one of the user events and the user activitiesidentified as in 4-3 on the cloud server, as in 4-5.

As an example, one of the identified risk scenarios can include the user1 attending a concert, a sporting event, a street festival, or apolitical march that has a high risk for the consumer electronics device3 because the user 1 is likely to capture a video or a photograph whileholding the consumer electronics device 3 at an elevated height orbecause large crowds associated with such a high risk event increase thelikelihood of the consumer electronics device 3 being stolen. Thesoftware application 2 can retrieve the identified risk scenario (e.g.concert attendance) and monitor the activities of the user 1 through theconsumer electronics device 3 to determine whether the user 1 haspurchased or is purchasing a ticket to the concert, for example, bymonitoring the user's 1 internet browsing, determining that the consumerelectronics device 3 received an email confirming a ticket purchase, orby monitoring the user's 1 text messages. In response to detecting thatthe user 1 purchased the ticket to the concert, for example, thesoftware application 2 can identify a match with the identified riskscenario and can register the user purchasing the concert ticketpurchase on the cloud server, as in 4-5.

As another example, one of the identified risk scenarios can include theuser 1 traveling internationally or to another high risk location. Thesoftware application 2 can retrieve the identified risk scenario (e.g.international travel) and monitor the activities of the user 1 todetermine whether the user 1 purchased a ticket to, reserved lodging in,or is physically present in an international location, a specificcountry particularly associated with risk (e.g. a developing country),or a risky or unsafe geographic location (e.g. a high crimeneighborhood), for example, by monitoring a destination address enteredby the user 1 into navigation software (e.g. Waze, Google Maps) or bymonitoring GPS coordinates of the consumer electronics device 3 relativeto GPS coordinates of the international location, the specific countryparticularly associated with risk, or the risky or unsafe geographiclocation. In response to detecting the user 1 purchasing the ticket tothe international location, for example, the software application 2 canidentify a match with the identified risk scenario and can register theuser 1 purchasing the ticket to the international location on the cloudserver, as in 4-5.

In some embodiments, when the software application 2 determines that oneof the user events and the user activities matches one of the identifiedrisk scenarios, the protection and insurance offering system 7 cangenerate a notification message to the consumer electronics device 3that includes an offer to the user 1 to purchase added protection orinsurance at any time prior to the user attending or travelling to theone of the identified risk scenarios to provide enhanced protection orheightened insurance for any or all portions of the user attending ortravelling to the one of the identified risk scenarios.

Like FIG. 5 , FIG. 6 is a flow diagram of a method 600 for adjustingrisk and generating warnings in accordance with disclosed embodiments,for example, by monitoring the user activities of the user 1 withinother applications executed by the consumer electronics device 3. Indoing so, the method 200 can identify risky behavior of the user 1through the consumer electronics device 3 and offer an insurance orprotection plan through the protection and insurance offering system 7for more than just the consumer electronics device 3. For example, theprotection and insurance offering system 7 can offer insurance orprotection for data stored on the consumer electronics device 3,stationary electronics in a home of the user 1, or actions of the user1.

As seen, the method 600 can include starting an actions monitoringprocess, as in 10-1. In some embodiments, the actions monitoring processcan include a background service that operates in conjunction with thebackground service described in connection with FIG. 2 or the eventdetection process described in connection with FIG. 5 . After beginningthe actions monitoring process, the method 600 can include the softwareapplication 2 identifying applications and actions that have apertinence for insurance from a database, as in 10-2, and identifyingthe user events and the user activities, as in 4-2, to determine whetherany of the user events and the user activities matches any of theapplications and actions that have a pertinence for insurance, as in10-3. The method 600 can determine the user activities by monitoring auser interface or touchscreen of the consumer electronics device 3. If,as in 10-4, none of the user events and the user activities identifiedas in 4-2 matches the applications and the actions identified as in10-2, then the method 600 can include the software application 2continuing to monitor for the user events and the user activities, as in4-2. However, if, as in 10-4, one of the user events and the useractivities identified as in 4-2 matches one of the applications and theactions identified as in 10-2, then the method 600 can include thesoftware application 2 registering the one of the user events and theuser activities identified as in 4-3 (see FIG. 5 ) on the cloud server,as in 4-5.

Finally, the method 600 can include determining whether the one of theuser events and the user activities identified as in 4-2 requires anotification message for warning the user 1, as in 10-5. If so, then thenotification message can be generated and audibly or visibly presentedto the user 1, as in 10-6.

As an example, one of the applications and the actions identified as in10-2 can include an application that controls a home security system ofthe user 1. When the software application 2 determines, through GPSdata, that the user 1 is away from home, the software application 2 candetermine whether the user 1 has armed the home security system via theapplication that controls the home security system. When the user 1 hasfailed to arm the home security system via the application that controlsthe home security system, the software application 2 can generate anotification message to remind the user 1 to arm the home securitysystem via the application that controls the home security system.Failure to consistently arm the home security system or respond toreminders to do so can result in increased costs in the risk basedpolicy offering 8.

As another example, one of the applications and the actions identifiedas in 10-2 can include an application that backs up data stored on theconsumer electronics device 3. The software application 2 can monitorthe user 1 backing up the consumer electronics device 3 via theapplication that backs up data stored on the consumer electronics device3, and upon a failure to backup within a predetermined period of time,the software application 2 can offer a service to back up the datastored on the consumer electronics device 3 via the risk based policyoffering 8 and/or automatically back up the consumer electronics device3.

Generally, the cost to repair or replace the consumer electronics device3 drops precipitously over time. For example, FIG. 7 is a graph plottingdevice depreciation for an iPhone 6s mobile device, an iPhone X mobiledevice, and a Samsung Galaxy S6 mobile device. As shown in FIG. 7 ,70-80% of a device's value is lost after one year. Accordingly, systemsand methods disclosed herein can offer a discounted insurance plan basedon the device depreciation.

FIG. 8 is a flow diagram of a method 800 for accounting for devicedepreciation in accordance with disclosed embodiments, for example, bybasing a price of an insurance offering on depreciated value. Forexample, the consumer electronics device 3 can depreciate from a launchdate regardless of when the consumer electronics device 3 was purchasedbecause newer versions are always being developed. In this regard, theiPhone 8 launched in October, 2017 at a release price of $750 andcontinued to sell at that price for an extended period of timethereafter. Nevertheless, a value of the iPhone 8 depreciatedapproximately 1% per week with a floor determined by demand in themarketplace.

As seen in FIG. 8 , the method 800 can include determining a make and amodel of the consumer electronics device, as in 801, and identifying areplacement cost percentage of the consumer electronics device 3, as in802. In some embodiments, the replacement cost percentage can beidentified as follows:

${{Replacement}\mspace{14mu}{cost}\mspace{14mu}{percent}\mspace{14mu}{reduction}} = {\frac{\left( {{{release}\mspace{14mu}{price}} - {ASP}} \right)}{{release}\mspace{14mu}{price}}*100}$where the release price can be a retail price of the consumerelectronics device 3 when the consumer electronics device 3 was firstlaunched and where ASP can be an average selling price of the consumerelectronics device 3 on a secondary market. ASP can be updated monthlyor at some other periodic interval. In some embodiments, the method 800can factor additional variables into the replacement cost percentage,such as months since the launch date, device attributes, seasonaleffects, macro variables, and worldwide or geographical calamities (e.g.political turmoil that affects trade or a typhoon in Asia that haltstrading, thereby impacting a supply of consumer electronics devices inNorth America), each of which can be assigned a coefficient andincorporated into the equation used for identifying the replacement costpercentage.

Then, the method 800 can include comparing the replacement costpercentage to a threshold value as in 804. When the replacement costpercentage exceeds the threshold value, the method 800 can includeextending a discounted insurance offering to the user 1, as in 806. Forexample, if a smartphone was purchased on Jan. 1, 2018 for $1,000 (e.g.release price) and is valued on Dec. 1, 2019 at $300 (e.g. ASP), thenthe replacement cost percentage can be 70%, and the method 800 can offerthe discounted insurance offering with a 50% discount.

Some technology for consumer electronics devices can increase adurability of the consumer electronics device 3. For example, somesmartphones can include organic light emitting diode (OLED) displays. Inaddition to higher display quality, OLED displays can have higherdurability and a lower propensity for cracks and scratches. Indeed,testing has shown that an iPhone 7 having an OLED screen breaks only 6%of the time when dropped from a distance of ten feet whereas an iPhone 6having an LCD screen breaks 74% of the time when dropped from the samedistance and that the iPhone 7 has a decreased chance of damage to aback glass, a back camera, a front camera, and a loud speaker ascompared to the iPhone 6. Accordingly, systems and methods disclosedherein can offer a discounted insurance plan based on device durability.

FIG. 9 is a flow diagram of a method 900 for accounting for devicedurability in accordance with disclosed embodiments, for example, bybasing a price of an insurance offering on the device durability. Asseen, the method 900 can include starting a risk assessment process, asin 6-1. In some embodiments, the risk assessment process can include abackground service that operates in conjunction with the backgroundservice described in connection with FIG. 2 , the event detectionprocess described in connection with FIG. 5 , or the actions monitoringprocess 10-1 described in connection with FIG. 7 . After starting in therisk assessment process, the method 900 can include determining a makeand a model of the consumer electronics device 3, as in 6-2, forexample, by referencing data stored on the consumer electronics device3, a profile of the user 1 stored by the protection and insuranceoffering system 7, or a TCP/IP packet sent over the Internet. Then, themethod 900 can include retrieving a device durability index ratingassociated with the make and the model from a device durability indexdatabase, as in 6-3, and determining whether the device durability indexrating exceeds a predetermined threshold value, as in 6-4. When thedevice durability index rating exceeds the predetermined thresholdvalue, as in 6-4, the method 900 can include the protection andinsurance offering system 7 offering a discounted rate.

In some embodiments, systems and methods disclosed herein can alsoinclude creating and populating the device durability index databasewith a respective device durability index rating for each of a pluralityof makes and each of a plurality of models based on significantdiagnostic testing of the plurality of makes and the plurality of modelsand aggregate data thereof. Additionally or alternatively, systems andmethods disclosed herein can identify the respective device durabilityrating for each of the plurality of makes and each of the plurality ofmodels from a respective part durability rating for each of a pluralityof parts forming a respective device.

In some situations, the consumer electronics device 3 may be broken, butthe user 1 may wish to protect remaining functional components of theconsumer electronics device 3. FIG. 10 is a flow diagram of a method1000 for generating a protection plan based on device diagnostics inaccordance with disclosed embodiments, for example, by generating aspecialized insurance plan based on results of a diagnostics test.

As seen, the method 1000 can include the software application 2executing a diagnostics test, as in 9-2 and, based on results of thediagnostics test, determining whether all components of the consumerelectronics device 3 are functional, as in 9-3. When the diagnosticstest indicates that all components of the consumer electronics device 3are fully functional, the method 1000 can include the softwareapplication 2 generating a report indicative thereof, and theprotections and insurance offering system 7 can offer a standard rateinsurance plan, as in 9-4. However, when the diagnostics test indicatesthat one or more of the components of the consumer electronics device 3is non-functional, the software application 2 can generate a report thatidentifies an exclusionary list that includes the components of theconsumer electronics device 3 that failed the diagnostics test, as in9-5. Then, the method 1000 can include the software application 2transmitting the exclusionary list to the protections and insuranceoffering system 7, which can use the exclusionary list to reference aprotection offering database, as in 5-3, and provide a specialized offerwith exclusions, as in 9-6.

For example, if the diagnostics test reveals that a front camera of theconsumer electronics device 3 is non-functional, then the protection andinsurance offering system 7 can offer an insurance plan that excludesprotection of the front camera and is discounted accordingly. In someembodiments, an amount of a discount can be based on a percentage ofinsurance claims that claim damage to such a non-functional component(e.g. the front camera). For example, if relatively few insurance claimsclaim damage to the front camera (e.g. 10%), then a price of theinsurance plan can be discounted a relatively small amount (e.g. 5%discount). Alternatively, if a screen of the consumer electronics device3 is cracked and, therefore, the non-functional component, and arelatively high number of insurance claims claim damage to the screen(e.g., 75%), then the discount can be higher (e.g. 45% discount).

In some embodiments, the discount can be based on a relative value ofthe non-functional component toward an overall value of the consumerelectronics device 3. Additionally or alternatively, in someembodiments, the discount can be based on a price to repair thenon-functional component. For example, if the price to repair thenon-functional component is higher than functioning components of theconsumer electronics device 3, then the discount can be higher than ifthe price to repair the non-functional component were lower than thefunctioning components.

The systems and methods disclosed herein present a substantialadvancement over the prior art by identifying a price to insure aconsumer electronics device based on data from sensors of the consumerelectronics device itself. Furthermore, the systems and methodsdisclosed herein improve upon the prior art by continually monitoringand detecting data related to risk-creating events and actions of theconsumer electronics device, the health of the consumer electronicsdevice, and the overall condition of the consumer electronics device viaa software application executing and operating in the background of theconsumer electronics device without disrupting other functions orapplications executed by the consumer electronics device. Finally, thesystems and methods disclosed herein are an improvement to the prior artbecause the systems and methods disclosed herein interact with thesensors of the consumer electronics device itself, thereby facilitatingthe consumer electronics device regularly monitoring its own health toprotect itself from damage.

Although a few embodiments have been described in detail above, othermodifications are possible. For example, the logic flows described abovedo not require the particular order described or sequential order toachieve desirable results. Other steps may be provided, steps may beeliminated from the described flows, and other components may be addedto or removed from the described systems. Other embodiments may bewithin the scope of the invention.

From the foregoing, it will be observed that numerous variations andmodifications may be effected without departing from the spirit andscope of the invention. It is to be understood that no limitation withrespect to the specific system or method described herein is intended orshould be inferred. It is, of course, intended to cover all suchmodifications as fall within the spirit and scope of the invention.

What is claimed is:
 1. A method for automatic consumer electronicsdevice protecting, the method comprising: determining, by at least oneprocessor from data stored on a consumer electronics device ortransmitted by the consumer electronics device, a make of the consumerelectronics device; determining, by the at least one processor from datastored on the consumer electronics device or transmitted by the consumerelectronics device, a model of the consumer electronics device;generating sensor data via at least one sensor of the consumerelectronics device, the sensor data comprising at least accelerometerdata from an accelerometer of the consumer electronics device;identifying, by the at least one processor, a thrown threshold valueassociated with the accelerometer data of the sensor data; monitoringthe sensor data from the consumer electronics device, by the at leastone processor via a software application operating on the consumerelectronics device, to continually detect a number of drop events fromthe sensor data, wherein the at least one processor detects each dropevent represented by the number of drop events by at least comparing aportion of the sensor data over at least one time interval with at leastone threshold value indicative of a drop event, the at least onethreshold value determined based at least in part on the make of theconsumer electronics device and the model of the consumer electronicsdevice, and wherein detecting the number of drop events comprises:detecting, by the at least one processor, at least a portion of theaccelerometer data that (1) indicates an acceleration falling below thethrown threshold value or (2) indicates an acceleration that increasesbefore falling below a lower threshold value of the at least onethreshold value; and in response, determining that the at least theportion of the accelerometer data indicates at least one throw eventdistinct from the at least one threshold value indicative of the dropevent, wherein the number of drop events does not include the at leastone throw event; determining, by the at least one processor, the numberof drop events within a time period; automatically causing displaying ofa notification message to a display of the consumer electronics devicein response to the number of drop events within the time periodexceeding a propensity threshold value, the notification messagecomprising instructions to prevent future damage to the consumerelectronics device based at least in part on the number of drop events;and causing automatic initiation, by the at least one processor, of anew backup of the consumer electronics device in response to adetermination that the number of drop events within the time period hasexceeded the propensity threshold value.
 2. The method of claim 1,wherein detecting the number of drop events from the sensor datacomprises: detecting, via a first sensor of the consumer electronicsdevice, a second portion of the accelerometer data during at least onetime interval; and detecting, by the at least one processor via thesoftware application operating on the consumer electronics device, atleast one drop event based at least in part by determining, during theat least one time interval, that the second portion of the accelerometerdata exceeds a first threshold value and that the second portion of theaccelerometer data then drops below a second threshold value within apredetermined second time interval.
 3. The method of claim 2, the methodfurther comprising: setting, by the at least one processor, the firstthreshold value and/or the second threshold value based at least in parton one or more of the make of the consumer electronics device and themodel of the consumer electronics device.
 4. The method of claim 2, themethod further comprising: detecting, via a second sensor of theconsumer electronics device, gyroscope data during the at least one timeinterval, wherein the gyroscope data comprises rotation data;validating, by the at least one processor, the gyroscope data during thepredetermined second time interval indicates the drop event bycalculating, via the software application, a geometric mean of arotation of the consumer electronics device using the rotation data anddetermining that the drop event was a damage-inducing drop event in aninstance in which the geometric mean of the rotation and an orientationindicated by the gyroscope data exceeds an impact threshold valueindicative of a drop on a hard surface and/or another damage-inducingdrop event; and returning an indication of the damage-inducing dropevent.
 5. The method of claim 2, the method further comprising:determining, by the at least one processor, that another portion of theaccelerometer data before each drop event represented in the number ofdrop events does not satisfy the thrown threshold value.
 6. The methodof claim 2, the method further comprising: detecting, by the at leastone processor, a soft drop event by at least: determining, by the atleast one processor during a first time interval, that another portionof the accelerometer data exceeds an intermediate threshold, wherein thenumber of drop events does not represent the identified soft drop event.7. The method of claim 1, wherein automatically causing displaying ofthe notification message to the display of the consumer electronicsdevice is further in response to a user risk profile that is updatedbased at least in part on the number of drop events, wherein thenotification message is an audio message or a visual message on theconsumer electronics device, and wherein the instructions to preventfuture damage to the consumer electronics device comprises a suggestedproactive action to prevent the future damage to the consumerelectronics device.
 8. The method of claim 1, the method furthercomprising: identifying, by the at least one processor, a high riskscenario associated with the consumer electronics device based at leastin part on the sensor data, wherein the high risk scenario comprises adrop rate greater than an average user, wherein the automaticallycausing displaying of the notification message to the display of theconsumer electronics device is further in response to the identifiedhigh risk scenario.
 9. The method of claim 1, the method furthercomprising: incrementing, by the at least one processor, the number ofdrop events within the time period as each drop event is continuallydetected during monitoring of the sensor data.
 10. The method of claim1, the method further comprising: continually receiving, by the at leastone processor, a new portion of accelerometer data, and continuallyattempting, by the at least one processor, to detect the drop event uponreceiving the new portion of accelerometer data by comparing at leastthe new portion of accelerometer data with the thrown threshold value.11. The method of claim 1, wherein the notification message furthercomprises an indication of damage caused by at least one drop eventrepresented by the number of drop events.
 12. The method of claim 1,wherein the make of the consumer electronics device and/or the model ofthe consumer electronics device is determined from a TCP/IP packetreceived via the consumer electronics device.
 13. The method of claim 1,the method further comprising: calculating, via the softwareapplication, a geometric mean of acceleration based at least in part onthe accelerometer data; and determining the drop event by at leastcomparing the geometric mean of acceleration with the at least onethreshold value indicative of a drop event.
 14. The method of claim 1,wherein to detect the drop event the method further comprises:determining, via the software application, that the accelerometer dataindicates the acceleration exceeded an upper threshold value of the atleast one threshold value and subsequently fell below a lower thresholdof the at least one threshold value within the at least one timeinterval.
 15. The method of claim 1, wherein to detect the drop eventthe method further comprises: determining, via the software application,that the accelerometer data indicates the acceleration initially fellbelow the lower threshold value, subsequently exceeded an upperthreshold value of the at least one threshold value, and subsequentlyfell below the lower threshold value.
 16. A system for automaticconsumer electronics device protecting, the system comprising: aconsumer electronics device having at least one sensor, the at least onesensor comprising an accelerometer configured to generate accelerometerdata; and at least one processor that is configured to execute computerprogram instructions to: (1) determine a make of the consumerelectronics device, and determine a model of the consumer electronicsdevice; (2) identify, by the at least one processor, a thrown thresholdvalue associated with the accelerometer data of the sensor data; (3)monitor the sensor data from the consumer electronics device, via asoftware application operating on the consumer electronics device, tocontinually detect a number of drop events from the sensor data, whereineach drop event represented by the number of drop events is detected byat least comparing a portion of the sensor data over a time intervalwith at least one threshold value indicative of a drop event, the atleast one threshold value determined based at least in part on the makeof the consumer electronics device and the model of the consumerelectronics device, and wherein to detect the number of drop events theat least one processor is configured to: (a) detect at least a portionof the accelerometer data that indicates an acceleration falling belowthe thrown threshold value or indicates an acceleration that increasesbefore falling below a lower threshold value of the at least onethreshold value; (b) in response to (3)(a), determine that the at leastthe portion of the accelerometer data indicates at least one throw eventdistinct from the at least one threshold value indicative of the dropevent, wherein the number of drop events does not include the at leastone throw event; (4) determine the number of drop events within a timeperiod; (5) automatically cause display of a notification message to adisplay of the consumer electronics device in response to the number ofdrop events within the time period exceeding a propensity thresholdvalue, the notification message comprising instructions to preventfuture damage to the consumer electronics device based at least in parton the number of drop events; and (6) cause automatic initiation of anew backup of the consumer electronics device in response to adetermination that the number of drop events within the time period hasexceeded the propensity threshold value.
 17. The system of claim 16, theat least one processor further configured to: identify a high riskscenario associated with the consumer electronics device indicated basedat least in part on the sensor data, wherein the high risk scenariocomprises a drop rate greater than an average user; automatically causedisplay of the notification message to the display of the consumerelectronics device in response to the identified high risk scenario. 18.The system of claim 16, the at least one processor further configuredto: calculate, via the software application, a geometric mean ofacceleration based at least in part on the accelerometer data; anddetermine the drop event by at least comparing the geometric mean ofacceleration with the at least one threshold value indicative of a dropevent.
 19. The system of claim 16, the at least one processor furtherconfigured to: automatically initiate, via the software application, anew backup of the consumer electronics device based at least in part onthe number of drop events.